Real-time facial expression recognition system

Facial expressions are visible manifestation of the affective state, cognitive activity and personality of a person. Over the last two decades, the advances in imaging and computing technology have led to significant research effort on facial expression recognition. In the final year project, the re...

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Main Author: Xu, Meng Yao
Other Authors: Huang Guangbin
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/64549
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-645492023-07-07T16:07:47Z Real-time facial expression recognition system Xu, Meng Yao Huang Guangbin Lin Zhiping School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Facial expressions are visible manifestation of the affective state, cognitive activity and personality of a person. Over the last two decades, the advances in imaging and computing technology have led to significant research effort on facial expression recognition. In the final year project, the recognition system is designed to recognise drivers’ expressions from a real-time video. As a crucial part of the future driving enhancement system, facial expression recognition could be used to analyse drivers’ emotion states so that it will predict risky driving behaviours. By providing proper corrections, some accidents could be avoided. To implement the face expression recognition, histogram-of-oriented-gradient (HOG) based object detector, active shape model (ASM) and extreme learning machines (ELM) algorithms are used in this project. The real-time recognition system could locate face regions, extract facial features and recognise basic human expressions that could be considered as an important study or exploration for the future driving safety enhancement. Bachelor of Engineering 2015-05-28T02:43:37Z 2015-05-28T02:43:37Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64549 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Xu, Meng Yao
Real-time facial expression recognition system
description Facial expressions are visible manifestation of the affective state, cognitive activity and personality of a person. Over the last two decades, the advances in imaging and computing technology have led to significant research effort on facial expression recognition. In the final year project, the recognition system is designed to recognise drivers’ expressions from a real-time video. As a crucial part of the future driving enhancement system, facial expression recognition could be used to analyse drivers’ emotion states so that it will predict risky driving behaviours. By providing proper corrections, some accidents could be avoided. To implement the face expression recognition, histogram-of-oriented-gradient (HOG) based object detector, active shape model (ASM) and extreme learning machines (ELM) algorithms are used in this project. The real-time recognition system could locate face regions, extract facial features and recognise basic human expressions that could be considered as an important study or exploration for the future driving safety enhancement.
author2 Huang Guangbin
author_facet Huang Guangbin
Xu, Meng Yao
format Final Year Project
author Xu, Meng Yao
author_sort Xu, Meng Yao
title Real-time facial expression recognition system
title_short Real-time facial expression recognition system
title_full Real-time facial expression recognition system
title_fullStr Real-time facial expression recognition system
title_full_unstemmed Real-time facial expression recognition system
title_sort real-time facial expression recognition system
publishDate 2015
url http://hdl.handle.net/10356/64549
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